Framework
Acceptance criteria tell engineering: "This feature is done when..."
For AI features, AC must include:
- Functional: MVP works (recommendations generate, predictions work)
- Accuracy: Meets success threshold (80% accuracy, <200ms latency)
- Safety: No unacceptable failure modes manifest (no hallucinations on edge cases)
- Monitoring: Metrics dashboards live and alerting configured
- Rollback: Kill-switch exists and tested
Examples
Bad AC: "Recommendations feature is complete"
Good AC:
- Recommendations generate for 95% of users
- Accuracy >= 75% on holdout test set
- Latency < 300ms p99
- Hallucinations rate < 0.5%
- Monitoring dashboard live with alerts
- One-click disable flag tested end-to-end
- User thumbs-down button present and logging
Key Takeaways
- AC should be testable, measurable, unambiguous. "Works" is not AC. "Accuracy > 75%" is AC.
- Include safety + monitoring in AC. If you ship without monitoring, you fail AC.